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Featured in Development

Alex Bradbury gives an overview of the status and development of RISC-V as it relates to modern operating systems, highlighting major research strands, controversies, and opportunities to get involved.

Featured in Architecture & Design

Will Jones talks about how Habito, the leading digital mortgage broker, benefited from using Haskell, some of the wins and trade-offs that have brought it to where it is today and where it's going next. He also talks about why functional programming is beneficial for large projects, and how it helps especially with migrating the data store.

Featured in AI, ML & Data Engineering

Katharine Jarmul discusses research related to fair-and-private ML algorithms and privacy-preserving models, showing that caring about privacy can help ensure a better model overall and support ethics.

Featured in Culture & Methods

This personal experience report shows that political in-house games and bad corporate culture are not only annoying and a waste of time, but also harm a lot of initiatives for improvement. Whenever we become aware of the blame game, we should address it! DevOps wants to deliver high quality. The willingness to make things better - products, processes, collaboration, and more - is vital.

Featured in DevOps

Service mesh architectures enable a control and observability loop. At the moment, service mesh implementations vary in regard to API and technology, and this shows no signs of slowing down. Building on top of volatile APIs can be hazardous. Here we suggest to use a simplified, workflow-friendly API to shield organization platform code from specific service-mesh implementation details.

Amazon Alexa Skill CLI and Management API to Streamline Development

Amazon has announced a new API and command-line tool to make it possible to create, update, test, and submit Alexa skills.

Previously to the introduction of Alexa Skill CLI and Management API, the only option for developers to manager their skills was through the Amazon Skill Developer Portal, which was somewhat cumbersome to use for a number of reasons, such as slow interface, information scattering across several pages, limited editing capabilities, etc. More importantly, using the Developer Portal, developers had to manually execute all steps involved in creating or updating a skill. The Alexa Skill CLI will instead make it possible to automate all those steps using a script or plugging it into a continuous delivery pipeline. According to Amazon, all features of the Alexa Skills Kit are supported, including account linking integration or permission management.

For example, after installing and initializing the Alexa Skills CLI, you can create and deploy a new “Hello World” skill using the commands:

ask new
ask deploy

The ask new command creates two files, skill.json containing the skill’s metadata, and models/en-US.json with a sample interaction model. If a skill uses AWS Lambda, the deploy command will also automatically deploy the skill’s code in addition to updating its metadata and interaction model.

An area that can greatly benefit from the automation possibilities provided by the Alexa Skills CLI is testing skill invocations, which was previously only possible by manually entering each test utterance in the skill simulator provided in the Skill Portal. Using the Alexa Skills CLI, you can test an utterance by running:

According to Amazon, the Alexa Skill Management API, which provides the foundations for the Alexa Skills CLI, will open up many possibilities to create new tools that help developers design and build their skills, skipping the manual copy-paste phase that is required when interacting with the Developer Portal.